A Study of the Relationship between the Dynamic Viscosity and Thermodynamic Properties of Palm Oil, Hydrogenated Palm Oil, Paraffin, and Their Mixtures Enhanced with Copper and Iron Fines.

The article presents the results of phase transition studies in which the following substances and their mixtures were tested: 100% palm oil, 100% paraffin, 100% hydrogenated palm oil, 50% palm oil + 50% paraffin, 50% hydrogenated palm oil + 50% palm oil, 33% hydrogenated palm oil + 33% palm oil + 33% soft paraffin, 20% hydrogenated palm oil + 30% palm oil + 50% soft paraffin, 50% hydrogenated palm oil + 50% palm oil + copper, and 50% hydrogenated palm oil + 50% palm oil + iron. The measurements were carried out on a station for testing phase-change materials (PCMs) designed specifically for the analysis of phase changes. Viscosity values were also determined for the tested materials, and their potential impact on heat accumulation was assessed. The primary goal of the experiment was to determine some key thermodynamic parameters, including transition time, transition heat, specific heat, and dynamic viscosity at 58 °C. A one-way ANOVA test confirmed the statistical significance of minimum transition temperature, maximum transition temperature, and phase transition time, validating the reliability and utility of the results. The melting point, crucial for applications involving phase changes, was identified as an important factor. The careful selection of components allows for the customization of properties tailored to specific applications. A significant result is that the analyzed substances with higher specific heat values tend to have a higher average dynamic viscosity. The Pearson correlation coefficient of 0.82 indicated a strong positive association between the average dynamic viscosity and the heat of fusion of the substances examined. This suggests that changes in the heat of fusion significantly influence alterations in dynamic viscosity. Substances with higher specific heat values tend to exhibit higher average dynamic viscosity, emphasizing the direct impact of composition on viscosity.

Using expert-reviewed CSAM to train CNNs and its anthropological analysis.

Machine learning methods for the identification of child sexual abuse materials (CSAM) have been previously studied, however, they have serious limitations. Firstly, the training sets used to train the appropriate machine learning algorithms were not previously annotated by a forensic expert in anthropology. Secondly, previously presented solutions have rarely used models trained using real pornographic content involving children. Thirdly, previous studies have not presented a detailed justification for the classification decisions made, which is important due to the recent guidelines of the European Commission (Artificial Intelligence Act). The aim of the study was to train convolution neural networks (CNNs) using expert-labelled CSAM images and thereby identify the elements of the body and/or the environment that are critical for classifications by the neural network. To train and evaluate machine learning models, we used 60,000 images equally divided into four classes (CSAM images, images displaying sexual activity involving adults, images of people without sexual activity, and images not containing people). We used four neural network architectures: MobileNet, ResNet152, xResNet152 and its modification ResNet-s, designed for the purpose of research. The trained models provided high accuracy of classifying CSAM images: xResNet152 (F1 = 0.93, 92,8%), xResNet-s (F1 = 0.93, 93,1%), ResNet152 (F1 = 0.90, 91,39%), MobileNet (F1 ranged from 0.85 to 0.87, accuracy ranged from 86% to 87%). The results of the conducted research suggest that using expert knowledge (in sexology and anthropology) significantly improved the accuracy of the models. In regard to further anthropological analysis, the results indicate that the breasts, face and torso are crucial areas for the classification of pornographic content with children's participation. Results suggests that the ResNet-s neural network may be a reliable tool for clinical work and to support the work of experts witnesses in the field of anthropology. The study design received a positive opinion of the Ethics Committee of the Faculty of Mathematics, Informatics and Mechanics of the University of Warsaw. The clinical material was used for research purposes with the consent of the relevant prosecutor's offices. Authors provided free version of Windows application to classify CSAM for forensic experts, policemen and prosecutors at the OSF repository (DOI: 10.17605/OSF.IO/RU7JX).

Behavioral genetics of temporal framing: Heritability of time perspective and its common genetic bases with major personality traits.

OBJECTIVE: The present study aimed to provide a seminal behavioral genetic analysis of time perspectives (TPs). Moreover, we intended to investigate the magnitude of genetic vs. environmental components of the well-established assocations between TPs and personality features. BACKGROUND: Individual differences in temporal framing processes, referred to as TPs, are vital psychological and behavioral outcomes. Although proponents of TP theory emphasize mainly environmental origins of the tendencies to adopt certain TPs, research provides evidence for marked associations between the temporal dimensions and major personality traits that are known to be heritable. Hence, it was essential to empirically verify these claims. METHOD: The article reports an analysis of genetic and environmental components of variance in TPs based on a study adopting a twin design, conducted on a sample of 393 pairs of twins (135 monozygotic and 258 dizygotic). RESULTS: Multivariate Cholesky decomposition supported an EA model assuming impacts of both unshared environmental factors (E) and additive genetic factors (A) across all TP dimensions, suggesting that the effects of shared environment on TPs are plausibly negligible. Heritability indices of TPs ranged between 0.51 for Present-Fatalistic and 0.62 for Present-Hedonistic, suggesting that the majority of the variance in TPs stems from genetic influences. Substantial genetic correlations were found between TPs and the Big Five personality traits. CONCLUSIONS: The findings provide further evidence for conceptualizing TPs as biologically based personality traits and challenge the claims that TP is mainly a product of culture, education, and personal experiences.

Emotional intelligence and mismatching expressive and verbal messages: a contribution to detection of deception.

Processing facial emotion, especially mismatches between facial and verbal messages, is believed to be important in the detection of deception. For example, emotional leakage may accompany lying. Individuals with superior emotion perception abilities may then be more adept in detecting deception by identifying mismatch between facial and verbal messages. Two personal factors that may predict such abilities are female gender and high emotional intelligence (EI). However, evidence on the role of gender and EI in detection of deception is mixed. A key issue is that the facial processing skills required to detect deception may not be the same as those required to identify facial emotion. To test this possibility, we developed a novel facial processing task, the FDT (Face Decoding Test) that requires detection of inconsistencies between facial and verbal cues to emotion. We hypothesized that gender and ability EI would be related to performance when cues were inconsistent. We also hypothesized that gender effects would be mediated by EI, because women tend to score as more emotionally intelligent on ability tests. Data were collected from 210 participants. Analyses of the FDT suggested that EI was correlated with superior face decoding in all conditions. We also confirmed the expected gender difference, the superiority of high EI individuals, and the mediation hypothesis. Also, EI was more strongly associated with facial decoding performance in women than in men, implying there may be gender differences in strategies for processing affective cues. It is concluded that integration of emotional and cognitive cues may be a core attribute of EI that contributes to the detection of deception.

[Expert's opinion on recommendations for water and other beverages consumption in elderly?]. / Stanowisko Grupy Ekspertów w sprawie zalecen dotyczacych spozycia wody i innych napojów przez osoby w wieku podeszlym.

The article encloses definition of water role and its body requirement, review of water balance and management in older persons regarding characteristic of this age group and concomitant disorders. Based on current literature and expert's opinion the recommendations for water consumption were expressed with estimation of insufficient apply and oversupply, evaluation of hydration state, domestic water sources in diet with accent on influence of proper hydration on comfort and good health.

Memories evoked by odors stimulating the olfactory nerve versus odors stimulating both the olfactory and trigeminal nerves: possible qualitative differences?

The purpose of the study was to establish whether autobiographical memories differ when a stimulus producing olfactory or/and trigeminal sensations was used as memory cue. The following hypothesis was formulated: memories evoked by odors activating the trigeminal and olfactory nerves would be subjectively assessed as more detailed, more clear, more important and less happy, as compared to memories evoked by odors activating exclusively the olfactory nerve. The hypothesis was based on the assumption that trigeminal odors are perceived as signaling potential threats for the organism. 30 Polish psychology students (M age = 22 yr.; 20 women, 10 men) were tested using six odors: three stimulating the olfactory nerve only and three stimulating both the olfactory and trigeminal nerves. Participants were asked whether a particular odor evoked any memories, and if they answered "yes," they were to respond to four questions related to the qualities of the memory. Ratings of memories evoked by odors that stimulated the olfactory nerve and those that stimulated both the olfactory and trigeminal nerves differed in clarity. Odors stimulating the trigeminal nerve may induce less happy memories. The results are promising as to the role of the trigeminal system in coding and retrieval of survival-related memories.

Discovery of antibody biomarkers using protein microarrays of tumor antigens cloned in high throughput.

Development of humoral and cellular immunity against self-cellular proteins in cancer patients is a phenomenal observation. The ability of immune system to sense the presence of the disease and to fight of the disease by generating autoantibodies against tumor antigens makes it a natural biosensor. Several screening technologies have been employed for the identification of tumor-specific antibodies in cancer patients. We have developed a multidimensional approach for the identification of diagnostic antigens that utilizes a combination of high-throughput antigen cloning and protein microarray-based serological detection of complex panels of antigens by exploiting the serum autoantibody repertoire directed toward tumor-associated antigens in cancer patients. Furthermore, validation of these antigens by different bioinformatics and biological approaches will reveal the diagnostic/prognostic utility of these antigens for personalized immunotherapy.

Autoantibody approach for serum-based detection of head and neck cancer.

Currently, no effective tool exists for screening or early diagnosis of head and neck squamous cell carcinoma (HNSCC). Here, we describe an approach for cancer detection based on analysis of patterns of serum immunoreactivity against a panel of biomarkers selected using microarray-based serologic profiling and specialized bioinformatics. We biopanned phage display libraries derived from three different HNSCC tissues to generate 5,133 selectively cloned tumor antigens. Based on their differential immunoreactivity on protein microarrays against serum immunoglobulins from 39 cancer and 41 control patients, we reduced the number of clones to 1,021. The performance of a neural network model (Multilayer Perceptron) for cancer classification on a data set of 80 HNSCC and 78 control samples was assessed using 10-fold cross-validation repeated 100 times. A panel of 130 clones was found to be adequate for building a classifier with sufficient sensitivity and specificity. Using these 130 markers on a completely new and independent set of 80 samples, an accuracy of 84.9% with sensitivity of 79.8% and specificity of 90.1% was achieved. Similar performance was achieved by reshuffling of the data set and by using other classification models. The performance of this classification approach represents a significant improvement over current diagnostic accuracy (sensitivity of 37% to 46% and specificity of 24%) in the primary care setting. The results shown here are promising and show the potential use of this approach toward eventual development of diagnostic assay with sufficient sensitivity and specificity suitable for detection of early-stage HNSCC in high-risk populations.